A recent Bloomberg BusinessWeek feature maintains that we are in the midst of yet another tech bubble. This time, writes BusinessWeek’s Ashlee Vance, “the hype centers on more precise ways to sell.”

Following on the success of Facebook and Google, Vance writes, investors are falling all over themselves to invest in like-minded social media companies even though some are unlikely to succeed in the long-term. No argument there. Some tech start-ups will fail while others will succeed, just as it’s always been.

He says this bubble is different, however, in that it isn’t likely to leave any significant, innovative technology behind after it pops, as did previous tech bubbles in the 1980’s (which led to more PC’s in the home) and late 1990’s (which resulted in an Internet infrastructure). The legacy of companies like Groupon, which offers group deals on goods and services, is “cute email,” Vance writes.

I couldn’t disagree more.

We may or may not be in the midst of a bubble, but it is not centered on, at least from a technology perspective, “more precise ways to sell.” That is the outcome many social media companies and others may be trying to achieve, but the current movement is really centered on finding new and innovative ways to make use of the mountains of data being created by man and machines every day.

No doubt the current Era of Big Data, as some call it, began at companies like Facebook and Google that wanted to better match advertisements to users. They developed new ways to store, process and analyze large volumes of user-generated data, like Hadoop and MapReduce, to do this. And if that’s where the innovation ended, Vance would have a valid point.

But that’s not where it ended. A handful of the same engineers and math geeks that created algorithms to better target online ads for Facebook, Google and others have since left to find new ways to apply analytics to Big Data. Jeff Hammerbacher, for example, who started out at Facebook, has since left and joined Cloudera, which is developing tools to make Hadoop more accessible to business users.

The legacy of the current tech environment will be better, smarter, faster ways to use data. Yes, that includes social media sites finding “more precise ways to sell,” as Vance puts it. But it will also include doctors using data analytics to make more precise diagnosis and engineers mining research data to find alternative fuel sources.

Vance leads his piece with Hammerbacher’s story, but he cites him as an exception, not the rule. For Vance, Hammerbacher is a “conscientious objector to the ad-based business model and marketing-driven culture that now permeates tech.”

The reality is not nearly as black and white. Some of the top minds in Silicon Valley will continue to use their skills to help social media companies better target ads. But others will and some already have turned their attention to applying Big Data techniques to other pursuits. Some, like Hammerbacher, are doing both.

Cloudera is working with its client First Life Research to build a searchable database of user-generated patient data to help researchers study the effects of various medications. But it is also helping its client Groupon – yes, the very same Groupon Vance cites in his piece – match daily group coupons to users.

It’s true, as Vance writes, that so far the number of Big Data start-ups focusing on something other than ad targeting advertising is small. But that number will grow, as there’s no lack of potential applications for Big Data analytics.

In his piece, Vance quotes Eric Schadt, the chief scientific officer at Pacific Biosciences, who is working to map gene and organ interactions. The work requires complex analysis of large volumes of data. “It won’t be old school biologists that drive the next leaps in pharma,” Schadt told Vance. “It will be guys like Jeff [Hammerbacher] who understand what to do with big data.”

Yes, the Era of Big Data began with social media sites analyzing user-generated data to better target ads. But it is evolving into an era where innovations in data analytics will help find cures to diseases and more efficient ways to power our homes.  That’s the true legacy of the Era of Big Data, bubble or no bubble.